1. Technical Field
The present invention relates generally to a positioning environment analysis apparatus and a method and system for predicting the location determination performance of a terminal using the apparatus and, more particularly, to an apparatus, method and system for analyzing the positioning environment of a designated service area using positioning resource information collected via site investigation and a positioning database (DB) upon configuring a platform for providing a Location-Based Service (LBS) in indoor space, thus analyzing the quality of a positioning service, such as the accuracy of a predicted location, in an integrated manner.
2. Description of the Related Art
With the rapid popularization of smart phones, a navigation device and some Social Network Services (SNS) which utilize smart phones require information about the location of users. Applications requiring such location information provide a navigation service using the provided user location information, or provide a Location-Based Service (LBS) such as a customized advertising service. Accordingly, a system for accurately determining the location of a user is urgently required in order to provide such a service.
To satisfy this requirement, in the case of outdoor spaces, a Global Positioning System (GPS) has been developed, and thus it is possible to very accurately determine locations in most areas, except for some downtown areas in which there are many buildings. However, in the case of indoor spaces, research into systems capable of accurately determining locations to such an extent that the systems are applicable to actual commercial services have been still conducted, and such systems are under development.
Meanwhile, one of the advantages obtained by the advent of smart phones is that the number of wireless Local Area Network (WLAN) (Wi-Fi) Access Points (APs) usable in indoor spaces has rapidly increased. In particular, in urban areas, Wi-Fi communication is available in most indoor spaces, and is readily accessible. In conformity with this tendency, research into indoor location determination (positioning) methods, which use previously and widely installed Wi-Fi networks, has been actively conducted.
One of various proposed location determination methods is a scheme for acquiring Received Signal Strength Indicator (RSSI) characteristics of Wi-Fi signals for respective points in a service area via detailed prior site investigation of the area and comparing the acquired RSSI characteristics with the RSSI characteristics of signals received by the user at a subsequent location determination step. This scheme is also referred to as “RF fingerprinting”, because the physical characteristics of radio waves are different from each other at respective points in indoor space, similar to the unique patterns of fingerprints of respective persons, and such patterns are compared with the pattern of signals received by the user. (P. Bahl and V. N. Padmanabhan. “RADAR: an in-building RF-based user location and tracking system,” in INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, 2000, pp. 775-784, vol 2).
More specifically, with the explosive popularization of Wi-Fi communication, in many indoor spaces, signals from multiple APs may be simultaneously received at one location. Radio waves, such as Wi-Fi signals, exhibit a characteristic whereby the RSSI decreases with increasing distance from a transmitter. However, in such an environment, since the degrees of attenuation of signals transmitted from respective APs differ from each other, RSSI values for respective APs are measured differently. At each point in indoor space, the distances between the point and APs are different from each other, and thus RSSI values for respective APs exhibit different characteristics at respective points. In this way, if the RSSI values expected to be received by the user at respective points are arranged and stored in a database (DB), the RSSI values may be used to determine the location of a pattern most similar to that of a received Wi-Fi signal to be the location of the user when the user receives the Wi-Fi signal.
Since indoor spaces have complicated structures due to the presence of ceilings, walls, etc., signals are subjected to series multipath fading, thus exhibiting very complicated signal characteristics. Therefore, pattern comparison-based positioning generally shows much better performance than other distance estimation or coverage-based positioning schemes. Further, due to such signal characteristics, it is very difficult to predict RSSI values at individual points, it is important to acquire accurate patterns. Accordingly, for location determination with high accuracy, a scheme for constructing a DB having physical attribute patterns by performing prior site investigation of a service area is generally performed.
In this way, radio waves such as Wi-Fi signals exhibit different physical characteristics at respective points in indoor space. Thus, when patterns related to the physical characteristics are arranged into a DB, the location of the user may be determined via subsequent pattern comparison. Infrastructure elements that can be used at this time are defined as “positioning resources”, which are not limited to WI-Fi resources. IndoorAtlas has proposed a scheme for utilizing pieces of geomagnetic pattern information at respective points, other than Wi-Fi signals, for location determination (https://www.indooratlas.com/features, see U.S. Patent Application Publication No. 2013-0179074 and U.S. Patent Application Publication No. 2013-0177208).
In addition, available positioning resources may include mobile communication networks such as a Long Term Evolution (LTE) network, Bluetooth, Near Field Communication (NFC), atmospheric pressure information, etc. In the following description of the specification, a description will be made based on positioning that uses Wi-Fi communication for the convenience of description, but the positioning resources described in the present specification are not limited to Wi-Fi resources, and may include the above-noted positioning resources. Also, a DB constructed based on such site investigation is called a “positioning database”, and hereinafter is also referred to as a “positioning DB”.
As described above, a problem arises in that, in order to construct an accurate positioning DB, site investigation of a wide area must be performed in advance, and major expense is required for such site investigation.
To solve this problem, a dynamic collection idea for collecting positioning resource information while moving by using a collection device that is capable of tracking the location of a collector via a sensor has been presented. Further, recently, the number of cases where smart phones are used as collection devices has increased (Y. Cho et al., “WARP-P: Wireless signal Acquisition with Reference Point by using simplified PDR—system concept and performance assessment,” Proc. the ION 2013 Pacific PNT Meeting, April 2013). Such ideas are advantageous in that the time and expense required to conduct a collection and site investigation procedure are effectively reduced, so that the data required to construct a positioning DB and a platform for an LBS using the DB (hereinafter referred to as an “LBS platform”) may be rapidly and inexpensively collected.
However, even if dynamic collection is utilized, it is difficult to construct an LBS platform sufficient to provide actual LBS using only a single site investigation, and procedures, such as that shown in FIG. 1, must be performed repetitively, and thus the problem of expense still remains.
Upon constructing an actual platform, it is difficult to construct a positioning DB that exhibits sufficient location determination performance using only a single site investigation in most indoor spaces. In an actual environment, the number of infrastructure elements such as Wi-Fi APs is not sufficient and, as a result, there may occur the case where available positioning resources are insufficient. Further, during a site investigation procedure, there are various factors that negatively influence location determination performance, such as human error, whereby a collector collects positioning resources while moving along an incorrect path or in an incorrect direction. Accordingly, once a positioning DB is created via site investigation, a repetitive procedure for verifying location determination performance through actual positioning testing in a designated service area, detecting problems, and re-collecting positioning resources must be performed.
Such a procedure is intended to search for the cause of dissatisfactory performance using only an existing DB and to solve the cause in such a way as to detect the positioning environment of a designated service area, respond to insufficient infrastructure elements by installing additional infrastructure at suitable places when infrastructure elements are insufficient in a specific area, and re-collect data when it is determined that collected data is insufficient or erroneous. For actual LBS, the location determination performance at a level required by the user must be guaranteed, and thus this task must be repetitively performed until the performance is satisfactory. This procedure entails a lot of time and expense. In particular, a collector must personally visit a designated service area, conduct tests, and subsequently make adjustments, whereby further additional expenses are incurred in the case where the designated service area is located far away from the collector. This also acts as a fundamental problem in business expansion, such as overseas expansion, from the standpoint of the location information service provider.
Furthermore, in actual service, various positioning resources may be included in a positioning DB. In addition, a problem arises in that, upon performing location determination using respective positioning resources, the location may be determined using various positioning schemes, and thus it is difficult to know which resources and which scheme must be used to realize optimal location determination performance. In particular, in indoor spaces, the physical characteristics of positioning resources may greatly differ from each other for respective points, and thus the optimal combination of positioning resources and positioning scheme may also differ for respective regions in a service area. Hence, even if the optimal location determination system has been configured for a single region, another combination must be found when moving to another region or another floor. To solve this problem, there is required a device or a system capable of more accurately analyzing a positioning environment because it is difficult to find an optimal combination merely by conducting simple site tests.
In summary, even if the expense required for a site investigation procedure is reduced, a problem still remains in that unnecessary expenses attributable to repetitive site investigation and site verification are incurred, unless a scheme for efficiently constructing a platform in the entire system construction procedure is provided. Further, even if a location determination platform is constructed as desired, a problem also remains in that it is also difficult to find an optimal location determination combination using only simple site tests so as to provide an optimal positioning service by effectively exploiting such a platform.
As preceding technology related to the present invention, there are Korean Patent No. 0441048 (entitled “Method and System for Accessing Mobile Communication Terminal Position Determination Performance of Mobile Terminal by Using Wireless Communication Network and A-GPS”), and U.S. Patent Application Publication Nos. 2008-0108371 and 2012-0112958.